University of Texas at Austin（得克萨斯大学奥斯汀分校）

PragReST: Self-Reinforcing Counterfactual Reasoning for Pragmatic Language Understanding

PragReST：用于语用语言理解的自我强化反事实推理

Jihyung Park, Minchao Huang, Leqi Liu, Elias Stengel-Eskin

机构 * The University of Texas at Austin（德克萨斯大学奥斯汀分校） 纠错

AI总结 提出PragReST框架，通过自监督构建语用问答数据、生成反事实推理轨迹，结合监督微调和强化学习提升大语言模型的语用推理能力，在四个基准上显著优于基线模型。

Comments First two authors contributed equally. Code and models: https://github.com/jihyung803/PragReST

Modeling Doppler Shifts in Radial-Velocity Data with Deep Learning toward Earth-mass Exoplanet Detection

利用深度学习建模径向速度数据中的多普勒频移以探测地球质量系外行星

Isidro Gómez-Vargas, Xavier Dumusque, Yinan Zhao, Khaled Al Moulla, Michael Cretignier

机构 * Department of Astronomy, University of Geneva 51 chemin de Pegasi, 1290 Versoix, Switzerland. Instituto de Astrofı\'isica de Andaluc\'ia (CSIC), Glorieta de la Astronom\'ia s/n, E-18008 Granada, Spain. Institute of Space Sciences (CSIC), Carrer de Can Magrans s/n, E-08193 Barcelona, Spain. Department of Astronomy, University of Texas at Austin, 2515 Speedway, Austin, TX 78712, USA. Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP, Rua das Estrelas, 4150-762 Porto, Portugal. Department of Physics, University of Oxford, OX13RH Oxford, UK. 纠错

AI总结 针对恒星活动干扰，提出结合物理启发光谱表示与深度学习的框架，通过交叉验证和遗传算法优化，可靠恢复振幅≥25 cm/s、周期10-550天的行星信号，并发布Python包doppleriann。

Comments 20 pages, 14 figures. Accepted for publication in Astronomy & Astrophysics